1. Field of Invention
The present invention relates to a method for registering images. More particularly, the present invention relates to a segment based image registration method, which uses the Fibonacci search.
2. Description of Related Art
Prior art mainly provides the Voronoi method and the Delaunay method for registering images.
The Voronoi method divides standard and examined images into Voronoi diagrams according to feature points thereof, forms vectors between every two adjacent feature points, and processes these features with discrete Fourier transforms to obtain vectors for every feature point. Then, the vectors of examined and standard images are compared to build similarity matrices of vector dimensions and magnitudes, and a transformation relationship between the two images is thereby derived.
The Delaunay method connects every feature point to form Delaunay triangles. Transformation relationships, such as scaling, rotation and translation, of sides of every Delaunay triangle in examined and standard images are compared to build four matrices, one of them being derived with the highest similarity, which is the optimal transformation parameter between the two images.
However, in the conventional Voronoi method, similarity matrices usually have wrong comparisons due to the deviations between the feature points. Moreover, if the line scan image segment is not large enough, the deviations are more serious, and the wrong comparisons caused thereby are increased. In the conventional Delaunay method, though the effects of the deviations between feature points are decreased, the sizes of matrices are usually quadratically enlarged with increasing image size or precision, and the enlargement greatly increases required computation time and memory space.
In engineering, computation time and memory space need to be specified, and it is hard to give considerations to both of them.
In many image registration applications, such as copper clay laminate inspections or document scans in fax machines, it is a general practice to use line scanning for image acquisition due to cost, precision, computation time, or even the construction of the entire equipment. The Voronoi and Delaunay methods often have to acquire images in segments because the sizes of images are too large, forcing the servo mechanism thereof to run and stop frequently and thus causing bad efficiency and serious errors.
In addition, in these situations, images may be twisted because of unbalanced forces of the servo mechanism, obstacles, user negligence, or variations in angles during image acquisition. The conventional machines ignore the twists in images due to lack of rectifying schemes, and cause inaccurate product and poor quality.